docstr: This test verifies that tracinCP and tracinCPFast
  influence methods required `inputs_dataset`.
docstr_tok: ["This","test","verifies","that","tracinCP","and","tracinCPFast","influence","methods","required","`","inputs_dataset","`","."]
code: def test_tracin_require_inputs_dataset(
      self,
      reduction,
      tracin_constructor: Callable,
  ) -> None:
      """
      This test verifies that tracinCP and tracinCPFast
      influence methods required `inputs_dataset`.
      """
      with tempfile.TemporaryDirectory() as tmpdir:
          (
              net,
              train_dataset,
              test_samples,
              test_labels,
          ) = get_random_model_and_data(tmpdir, unpack_inputs=False)
  
          criterion = nn.MSELoss(reduction=reduction)
  
          tracin = tracin_constructor(
              net,
              train_dataset,
              tmpdir,
              loss_fn=criterion,
              batch_size=1,
          )
          with self.assertRaisesRegex(AssertionError, "required."):
              tracin.influence(None, k=None)
  
file_path: captum/tests/influence/_core/test_tracin_validation.py
imports: import tempfile
  from typing import Callable
  import torch.nn
  from captum.influence._core.tracincp import TracInCP
  from captum.influence._core.tracincp_fast_rand_proj import TracInCPFast
  from parameterized import parameterized
  from tests.helpers.basic import BaseTest
  from tests.influence._utils.common import build_test_name_func, DataInfluenceConstructor, get_random_model_and_data
label_desc: Use image node_id 1 for calling the TestTracinValidator obj's underlying member method code with example usage: obj.test_tracin_require_inputs_dataset(reduction, tracin_constructor) without return types